"No Watermark Detected" Doesn't Mean It Isn't AI — The Asymmetry of SynthID
Images generated with Gemini carry a SynthID watermark. But a positive result and a negative result don't carry the same weight, and that asymmetry changes how you should track provenance.
Images Made With a Retiring Model Can Never Be Made Again — Tracking Regenerability in a Ledger
When Gemini's image generation models shut down on August 17, the assets you made with them can no longer be reproduced the same way. Here is the ledger design and code I use to decide, before the deadline, which assets are regenerable and which must be frozen.
Designing Batch Image Costs with Nano Banana 2 Lite: Decide by Measuring
How to fold the fastest, cheapest image model, Nano Banana 2 Lite, into high-volume generation: measuring per-image cost, a two-tier setup with a quality model, and retry handling grounded in real numbers.
Splitting Bulk Image Generation Cost in Two with Nano Banana 2 Lite: A Draft-and-Render Design
A two-tier cost design that routes first-pass generation to Nano Banana 2 Lite and final renders to the standard Nano Banana 2, with a minimal Python router you can adapt.
Before the August 17 Gemini Image Model Shutdown: Inventory Where You Actually Call Them First
Some Gemini image generation models retire on August 17. Before choosing a replacement, here is how to inventory which models are actually being called, and from where, using your request logs.
Putting Gemini image generation to work: from prompt design to thumbnails generated from video
A practical playbook for running Gemini image generation as a repeatable workflow instead of a lucky dip. From decomposing prompts into reproducible parts to the video-to-image automation unlocked by the Nano Banana 2 GA, with working code, a pre-publish quality gate, and a design that survives preview shutdowns.